DEM and terrain analysis to predict spatial pattern of SOC

Abstract

A simple approach to predict spatial pattern of SOC using a surrogate variable, soil Munsell value, with the aid of digital terrain analysis is presented. Digital elevation models (DEMs) were prepared using readily available digital topographic maps and then enhanced for a small sloping catchment in the Adelaide hills using plausibility algorithms. Seven terrain parameters were calculated from the DEMs. One hundred random points were identified across the 5.6 ha site and soil Munsell value was obtained. Correlation analysis showed elevation, specific catchment area, profile curvature, and wetness index influence soil Munsell value. It was also found that the application of plausibility algorithms to DEMs derived from topographic maps produced better correlation coefficients compared to unsmooth DEMs.